Often, indexes are utilized to facilitate effective navigation of the web. These indexes are frequently updated in accordance with changes to content of documents (e.g., web pages) that are within the scope of the index. In instances, web crawlers are employed to browse these documents at pre-determined time intervals to discover the changes to the content. Typically, the entire index is replaced each time the web crawler finds a change to content of a document, no matter how insignificant. Replacing the index usually involves pulling the index offline for an extended period and performing a full merge of the index. Additionally, while the subject index is offline several replicate indexes need to be created and relied upon to serve users when the subject index is down. Performing a full merge frequently (e.g., daily) is prohibitively expensive as it consumes a large amount of computing resources. Accordingly, indexes are not updated often enough to effectively track the changes to the content of the documents within their scope.
Because current solutions for updating an index to correspond with the content of the tracked documents, or other data, incur a substantial delay prior to updating, recent changes to terms of a web page (e.g., prices appended to items for online sale), or updates to other structured data (e.g., documents of various formats, non-web sources) are not reflected by the index. These shortcomings of the delayed updating are exaggerated when the index is expansive in size, covering a multitude of documents stored at a multitude of websites.